February 2008

October 2007

July 2007

June 2007

Detection, Tracking (2D, 3D) and Censusing

Censusing natural populations of bats is important for understanding the
ecological and economic impact of these animals on terrestrial
ecosystems. Colonies of Brazilian free-tailed bats (Tadarida
brasiliensis) are of particular interest because they represent some of the
largest aggregations of mammals known to mankind. It is challenging to census
these bats accurately, since they emerge in large numbers at night from their
day-time roosting sites. The group has used infrared thermal cameras to record
Brazilian free-tailed bats in California, Massachusetts, New Mexico, and Texas.
The group has developed automated image analysis methods that detect, track, and
count emerging bats.

Margrit Betke (BU Computer Science) and Thomas Kunz (BU Biology) and their
groups started collaborating on thermal video analysis of bats in 2002. In the
beginning of the project, the group focused on the problem of censusing bat
colonies. They were funded from 2003-2009 by an ITR grant from NSF (PI Kunz)
and are now funded by a 5-year HCC grant from NSF (PI Betke) and a new ONR MURI
(PI Morgansen, UW).

In 2004, the group started to employ two and later three cameras
to image emerging and foraging bats. Tracking multiple flying animals
in several camera views is challenging because data association must
be performed not only across time, as in single-camera or radar-based
tracking, but also across camera views; this is a multidimensional
assignment problem and is NP-hard. In contrast to previously
published work on 3D tracking from several cameras, the group's
state-of-the-art approach (1) uses a deferred-logic (not a sequential)
tracking framework, (2) can handle dense groups of targets, and (3)
does not assume that target motion is restricted to occur on a ground
plane.

The group applied a Greedy Randomized Search (GRASP) algorithm to the
multidimensional assignment problem of associating observations from
different cameras, minimizing the stereoscopic reconstruction error of
the associations and reducing the search space by considering an
epipolar neighborhood. GRASP provides an initial solution to the
assignment problem in a given time step, which is then improved by
considering GRASP associations across multiple time steps. This
approach has proven capable in addressing the difficult tracking and
assignment problems that involve hundreds of bats emerging from a cave
colony. It will cope effectively with the simpler tracking problem
that involve small numbers of foraging bats. The research team has
also tested a variant of the above algorithm which solves the
assignment and 3D reconstruction problem in a different order,
beginning with a predicted 3D position and assigning 2D observations;
this approach may be more appropriate in recordings with dense clutter
and more occlusions.